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Efficiently annotating object images with absolute size information using mobile devices / Martin Hofmann in International journal of computer vision, vol 127 n° 2 (February 2019)  

Public [article]  inInternational journal of computer vision > vol 127 n° 2 (February 2019) . - pp 207 - 224 Titre : Efficiently annotating object images with absolute size information using mobile devices Type de document : Article/Communication Auteurs : Martin Hofmann, Auteur ; Marco Seeland, Auteur ; Patrick Mäder, Auteur Année de publication : 2019 Article en page(s) : pp 207 - 224 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] appareil portable [Termes IGN] appariement automatique [Termes IGN] image numérique [Termes IGN] longueur focale Résumé : (Auteur) The projection of a real world scenery to a planar image sensor inherits the loss of information about the 3D structure as well as the absolute dimensions of the scene. For image analysis and object classification tasks, however, absolute size information can make results more accurate. Today, the creation of size annotated image datasets is effort intensive and typically requires measurement equipment not available to public image contributors. In this paper, we propose an effective annotation method that utilizes the camera within smart mobile devices to capture the missing size information along with the image. The approach builds on the fact that with a camera, calibrated to a specific object distance, lengths can be measured in the object’s plane. We use the camera’s minimum focus distance as calibration distance and propose an adaptive feature matching process for precise computation of the scale change between two images facilitating measurements on larger object distances. Eventually, the measured object is segmented and its size information is annotated for later analysis. A user study showed that humans are able to retrieve the calibration distance with a low variance. The proposed approach facilitates a measurement accuracy comparable to manual measurement with a ruler and outperforms state-of-the-art methods in terms of accuracy and repeatability. Consequently, the proposed method allows in-situ size annotation of objects in images without the need for additional equipment or an artificial reference object in the scene. Numéro de notice : A2018-600 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-018-1093-3 Date de publication en ligne : 24/05/2018 En ligne : https://doi.org/10.1007/s11263-018-1093-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92527 [article]